Why Retail Clinics Do Not Substitute for Emergency Department Visits and What This Means for Value-Based Care

Applying embedded program evaluation for care delivery transformation: An analysis of a home‐based urgent care program

Background

In 2014, Mass General Brigham, formerly Partners HealthCare, launched a novel urgent home‐based medical care program to provide rapid medical evaluation and treatment to homebound patients and older adults with frailty or limited mobility named the partners mobile observation unit (PMOU) program.

Methods

We conducted a pragmatic, embedded evaluation assessing the impact of PMOU on postreferral utilization and total medical expenditure (TME). We used propensity weighting and logistic regression to estimate the 30‐day adjusted odds ratios (ORs) of emergency department (ED) utilization and inpatient medical hospitalization for patients enrolled in PMOU (891 episodes of care) relative to those who were referred but not enrolled in the program (57 episodes of care) during the period of April 2017 to June 2018. We additionally conducted a difference‐in‐differences analysis assessing program impact on TME, comparing claims data 30 days pre/post referral.

Results

Despite positive trends, there were no statistically significant differences between the two groups with regard to postreferral ED visits or hospitalizations, with an OR of 0.83 (p = 0.56) and OR of 0.64 (p = 0.21), respectively. There was no statistically significant difference in pre/post referral TME for intervention relative to control episodes (p = 0.64). In post hoc analysis of control episodes, 75% received care elsewhere within 14 days of referral.

Conclusion

Although the results suggested positive trends, this analysis of this relatively mature program was unable to identify statistically significant reductions in ED visits, hospitalizations, or TME associated with the PMOU program. Future efforts to build home‐based urgent care programs or related programs targeting older adults with frailty or limited mobility should aim to improve patient targeting and identify opportunities to improve program operations and generate meaningful reductions in healthcare utilization and spending.

User Characteristics of a Low-Acuity Emergency Department Alternative for Low-Income Patients

Introduction

Emergency department (ED) use for healthcare that can be treated elsewhere is costly to the healthcare system. However, convenience settings such as urgent care centers (UCC) are generally inaccessible to low-income patients. Housing an UCC within a federally qualified health center (FQHC UCC) provides an accessible convenience setting for low-income patients. In 2014 a FQHC UCC opened two blocks from an ED in the same health system. Our goal was to compare characteristics, access to care, and utilization preferences for FQHC UCC and low-acuity ED patients through retrospective chart review and prospective surveying.

Methods

We completed a retrospective chart review of all patients from March 1, 2018–March 1, 2019, and compared characteristics of low-acuity ED patients (N = 3,911) and FQHC UCC patients (N = 12,571). We also surveyed FQHC UCC patients (N = 201) and low-acuity ED patients (N = 198) from January–July 2019.

Results

Half of FQHC UCC patients had private insurance. Of ED patients, 29% were aware of the FQHC UCC. Both groups had similar rates of primary care providers. The most common reason for choosing the ED was perceived severity, and for choosing a FQHC UCC was speed.

Conclusion

These findings show similarities and differences between these two patient populations. Future research is needed to determine utilization patterns and in-depth reasons behind them. Interventions that help patients decide where to go for low-acuity care may create more utilization efficiency.

Emergency Department Use across 88 Small Areas after Affordable Care Act Implementation in Illinois

Introduction

This study analyzes changes in hospital emergency department (ED) visit rates before and after the 2014 Affordable Care Act (ACA) insurance expansions in Illinois. We compare the association between population insurance status change and ED visit rate change between a 24-month (2012–2013) pre-ACA period and a 24-month post-ACA (2014–2015) period across 88 socioeconomically diverse areas of Illinois.

Methods

We used annual American Community Survey estimates for 2012–2015 to obtain insurance status changes for uninsured, private, Medicaid, and Medicare (disability) populations of 88 Illinois Public Use Micro Areas (PUMAs), areas with a mean of about 90,000 age 18–64 residents. Over 12 million ED visits to 201 non-federal Illinois hospitals were used to calculate visit rates by residents of each PUMA, using population-based mapping weights to allocate visits from zip codes to PUMAs. We then estimated n=88 correlations between population insurance-status changes and changes in ED visit rates per 1,000 residents comparing the two years before and after ACA implementation.

Results

The baseline PUMA uninsurance rate ranged from 6.7% to 41.1% and there was 4.6-fold variation in baseline PUMA ED visit rates. The top quartile of PUMAs had >21,000 reductions in uninsured residents; 16 PUMAs had at least a 15,000 person increase in Medicaid enrollment. Compared to 2012–2013, 2014–2015 average monthly ED visits by the uninsured dropped 42%, but increased 42% for Medicaid and 10% for the privately insured. Areas with the largest increases in Medicaid enrollment experienced the largest growth in ED use; change in Medicaid enrollment was the only significant correlate of area change in total ED visits and explained a third of variation across the 88 PUMAs.

Conclusion

ACA implementation in Illinois accelerated existing trends towards greater use of hospital ED care. It remains to be seen whether providing better access to primary and preventive care to the formerly uninsured will reduce ED use over time, or whether ACA insurance expansion is a part of continued, long-term growth. Monitoring ED use at the local level is critical to the success of new home- and community-based care coordination initiatives.